{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T01:55:55Z","timestamp":1769392555814,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,5,27]],"date-time":"2023-05-27T00:00:00Z","timestamp":1685145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science Committee of the Ministry of Education Science Culture and Sport of RA","award":["20TTCG-1E009"],"award-info":[{"award-number":["20TTCG-1E009"]}]},{"name":"Science Committee of the Ministry of Education Science Culture and Sport of RA","award":["ECS00000036"],"award-info":[{"award-number":["ECS00000036"]}]},{"name":"MUR\u2013M4C2 1.5 of PNRR","award":["20TTCG-1E009"],"award-info":[{"award-number":["20TTCG-1E009"]}]},{"name":"MUR\u2013M4C2 1.5 of PNRR","award":["ECS00000036"],"award-info":[{"award-number":["ECS00000036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Machine learning (ML) was used to assess and predict urban air temperature (Tair) considering the complexity of the terrain features in Yerevan (Armenia). The estimation was performed based on the Partial Least-Squares Regression (PLSR) model with a high number (30) of input variables. The relevant parameters include a newly purposed modification of spectral index IBI-SAVI, which turned out to strongly impact Tair prediction together with land surface temperature (LST). Cross-validation analysis on temperature predictions across a station-centered 1000 m circular area revealed quite a high correlation (R2Val = 0.77, RMSEVal = 1.58) between the predicted and measured Tair from the test set. It was concluded the remote sensing is an effective tool to estimate Tair distribution where a dense network of weather stations is not available. However, further developments will include incorporation of additional weather parameters from the weather stations, such as precipitation and wind speed, as well as the use of non-parametric ML techniques.<\/jats:p>","DOI":"10.3390\/rs15112795","type":"journal-article","created":{"date-parts":[[2023,5,27]],"date-time":"2023-05-27T16:17:33Z","timestamp":1685204253000},"page":"2795","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Machine Learning-Based Modeling of Air Temperature in the Complex Environment of Yerevan City, Armenia"],"prefix":"10.3390","volume":"15","author":[{"given":"Garegin","family":"Tepanosyan","sequence":"first","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6538-9171","authenticated-orcid":false,"given":"Shushanik","family":"Asmaryan","sequence":"additional","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"given":"Vahagn","family":"Muradyan","sequence":"additional","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"given":"Rima","family":"Avetisyan","sequence":"additional","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"given":"Azatuhi","family":"Hovsepyan","sequence":"additional","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3615-4023","authenticated-orcid":false,"given":"Anahit","family":"Khlghatyan","sequence":"additional","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"given":"Grigor","family":"Ayvazyan","sequence":"additional","affiliation":[{"name":"Centre for Ecological-Noosphere Studies, National Academy of Sciences of Armenia, Abovyan Street 68, Yerevan 0025, Armenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0044-2998","authenticated-orcid":false,"given":"Fabio","family":"Dell\u2019Acqua","sequence":"additional","affiliation":[{"name":"Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1080\/10095020.2021.2014765","article-title":"Artificial Intelligence and Remote Sensing for Spatial Prediction of Daily Air Temperature: Case Study of Souss Watershed of Morocco","volume":"25","author":"Meliho","year":"2022","journal-title":"Geo-Spat. 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